Characterizing Signal Behaviour Using Genetic Programming

@InCollection{jonsson:1996:csb,
author = "Per Jonsson and Jonas Barklund",
title = "Characterizing Signal Behaviour Using Genetic
Programming",
booktitle = "Evolutionary Computing",
publisher = "Springer-Verlag",
year = "1996",
editor = "Terence C. Fogarty",
number = "1143",
series = "Lecture Notes in Computer Science",
pages = "62--72",
address = "University of Sussex, UK",
month = "1-2 " # apr,
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-61749-3",
DOI = "doi:10.1007/BFb0032773",
size = "11 pages",
abstract = "Our overall goal is to detect automatically that a
signal begins to deviate from its previous behaviours,
using no other information than a sequence of samples
of the signal. In order to detect such changes we use
genetic programming to evolve an expression describing
how the signal varies over time. One major difficulty
when observing such signals is that they typically
contain noise and other disturbances. Such disturbances
makes it more difficult to find a useful expression
characterising the signal. We have derived a new method
that simultaneously evolves a numeral denoting the
number of neighbours to use in a moving average of the
signal, and an expression characterizing the smoothed
signal.",
notes = "The post-workshop proceedings of the 1996 AISB
workshop on evolutionary computing.",
affiliation = "Uppsala University Computing Science Department Box
311 751 05 Uppsala Sweden Box 311 751 05 Uppsala
Sweden",
}